Job description

At Plymouth Rock, a fast-growing, analytics-driven insurer, we believe data engineering can redefine how insurance operates. As the Data Engineer on our Enterprise Advanced Analytics team, you will be at the heart of this transformation. This high-visibility role is critical to our mission—empowering a team of top-tier data scientists to generate breakthrough insights that drive profitable growth, operational excellence, and competitive advantage. You will architect and manage the data pipelines that connect internal systems, third-party sources, and advanced analytical platforms, directly enabling our most strategic research initiatives. Working collaboratively across Data Science, IT, and business units, you will help shape how Plymouth Rock leverages cloud platforms, machine learning infrastructure, and modern data engineering to power enterprise-wide innovation. This is a unique opportunity to be both a builder and a thought leader in a hands-on role at the forefront of applied data science in the insurance industry. Responsibilities: • Serve as the subject matter expert of data engineering for the Enterprise Advanced Analytics team—designing, building, and optimizing data pipelines and workflows to empower advanced research and analytics. • Collaborate with key stakeholders across Data Science, IT and Business to automate and empower data and machine learning automation across our Personal Auto and Homeowner insurance business units. • Develop and enforce data governance and security protocols to uphold data quality and regulatory compliance. • Partner with IT on the transition to a cloud-based AWS data lake—championing new architectures and ways of working that harness cutting-edge technologies and unlock new analytical capabilities. • Create and manage data infrastructure to design, develop, and enhance data and analytics solutions and pipelines, enabling data-driven decision-making processes. • Design and implement automated pipelines for data and machine learning workflows and infrastructure with testing, versioning, and rollback capabilities. • Designing and building reusable processes and templates for packaging, testing, and deployment of internal python libraries, containers and data pipelines and machine learning workflows. • Stay current with industry trends and best practices in data and machine learning engineering and recommend improvements to existing processes. • Apply Python and SageMaker for advanced analytics, machine learning initiatives, and data science projects. • Familiarity with AWS security and governance tools (IAM, KMS, Lake Formation permissions, VPC design) to ensure data is secure and access-controlled • Play a pivotal role in shaping the future of Plymouth Rock’s data science and advanced analytics strategy while growing your career in a dynamic, innovation-driven environment. Qualifications: • Proven experience working with Snowflake, DBT, Fivetran, AWS Glue, Python, SageMaker, DB2, SQL Server, and Informatica technologies in a data engineering or analytics role with 5-6 years of experience. • A bachelor’s degree in computer science, Information Systems or related field. • 3+ years of related data/data platform or machine learning engineering experience with a focus on designing, building, and deploying automated pipelines and workflows. • Experience in building automated deployment pipelines and CI/CD workflows using Jenkins, GitHub Actions, Terraform, CloudFormation or similar tools. • Experience automating workflows using AWS cloud services (Lambdas, ECS, S3, Step Functions, Event bridge etc) • Experience with Docker, Padman and other containerization tools • Expert in Python, proficient in SQL, additional R and SAS knowledge and a bonus for legacy code. • Experience with data modeling and data warehousing. • Experience with cloud data platforms, Snowflake (preferable), AWS. • A design thinking and test-driven development mindset. • Experience with business intelligence tools and reporting solutions (Tableau etc.). • Knowledge of python packaging and distribution tools such as pip, poetry, setup tools, twine, etc. • Knowledge of data engineering and machine learning concepts, ETL/ELT, data lakes, data quality metrics • Strong communication and collaboration skills, with a track record of working effectively across technical and business teams. • Curiosity and commitment to continuous learning in emerging data engineering tools, platforms, and best practices. The pay range for this position is $98,000 to $142,000 annually. Actual compensation will vary based on multiple factors, including employee knowledge and experience, role scope, business needs, geographical location, and internal equity. Perks and Benefits: • 4 weeks accrued paid time off + 10 paid national holidays per year • Free onsite gym at our Boston Location • Tuition Reimbursement • Low cost and excellent coverage health insurance options that start on Day 1 (medical, dental, vision) • Robust health and wellness program and fitness reimbursements • Auto and home insurance discounts • Matching gift opportunities • Annual 401(k) Employer Contribution (up to 7.5% of your base salary) • Various Paid Family leave options including Paid Parental Leave • Resources to promote Professional Development (LinkedIn Learning and licensure assistance) • Convenient location directly across from South Station and Pre-Tax Commuter Benefits About the Company The Plymouth Rock Company and its affiliated group of companies write and manage over $2 billion in personal and commercial auto and homeowner’s insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent” #LI-SM1

Requirements

Must-haves

Serve as the subject matter expert of data engineering for the Enterprise Advanced Analytics team—designing, building, and optimizing data pipelines and workflows to empower advanced research and analytics.
Collaborate with key stakeholders across Data Science, IT and Business to automate and empower data and machine learning automation across our Personal Auto and Homeowner insurance business units.
Develop and enforce data governance and security protocols to uphold data quality and regulatory compliance.
Partner with IT on the transition to a cloud-based AWS data lake—championing new architectures and ways of working that harness cutting-edge technologies and unlock new analytical capabilities.
Create and manage data infrastructure to design, develop, and enhance data and analytics solutions and pipelines, enabling data-driven decision-making processes.
Design and implement automated pipelines for data and machine learning workflows and infrastructure with testing, versioning, and rollback capabilities.
Designing and building reusable processes and templates for packaging, testing, and deployment of internal python libraries, containers and data pipelines and machine learning workflows.
Stay current with industry trends and best practices in data and machine learning engineering and recommend improvements to existing processes.
Apply Python and SageMaker for advanced analytics, machine learning initiatives, and data science projects.
Familiarity with AWS security and governance tools (IAM, KMS, Lake Formation permissions, VPC design) to ensure data is secure and access-controlled
Play a pivotal role in shaping the future of Plymouth Rock’s data science and advanced analytics strategy while growing your career in a dynamic, innovation-driven environment.
Proven experience working with Snowflake, DBT, Fivetran, AWS Glue, Python, SageMaker, DB2, SQL Server, and Informatica technologies in a data engineering or analytics role with 5-6 years of experience.
A bachelor’s degree in computer science, Information Systems or related field.
3+ years of related data/data platform or machine learning engineering experience with a focus on designing, building, and deploying automated pipelines and workflows.
Experience in building automated deployment pipelines and CI/CD workflows using Jenkins, GitHub Actions, Terraform, CloudFormation or similar tools.
Experience automating workflows using AWS cloud services (Lambdas, ECS, S3, Step Functions, Event bridge etc)
Experience with Docker, Padman and other containerization tools
Experience with data modeling and data warehousing.
Experience with cloud data platforms, Snowflake (preferable), AWS.
A design thinking and test-driven development mindset.
Experience with business intelligence tools and reporting solutions (Tableau etc.).
Knowledge of python packaging and distribution tools such as pip, poetry, setup tools, twine, etc.
Knowledge of data engineering and machine learning concepts, ETL/ELT, data lakes, data quality metrics

Nice-to-haves

Expert in Python, proficient in SQL, additional R and SAS knowledge and a bonus for legacy code.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningawspythonsqlci/cddocker

Platform: adp-recruiting
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave

Wellness

Professional Development